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Seminar 3: Professor Manuel Riemer (University of Wilfrid Laurier University, Canada) - Engaging Students in Climate and Sustainability Action: A Community Psychology and Systems Perspective

2024· other· en· W6963031315 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2024
Typeother
Languageen
FieldArts and Humanities
TopicAcademic Writing and Publishing
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityPerspective (graphical)Context (archaeology)Transformative learningCommunity engagementEnvironmental educationAction (physics)Action research

Abstract

fetched live from OpenAlex

In this presentation, Dr Riemer will draw, among others, from his own teaching and research at the cross-section of community psychology, sustainability and systems science, and transformative education to explore key issues related to the engagement of students in climate and sustainability action. He will begin by presenting a theory of engagement for fostering collective action, which was developed in the context of the Youth Leading Environmental Change (YLEC) study conducted with countries from the global North and South. Dr Riemer will then apply this theory to specific pedagogical strategies intended to shift mental models, foster systems thinking, engage with sustainability and climate justice, and build action competence. He will conclude with some general considerations about student engagement in the current context of universities, including an increasing prevalence of negative eco-emotions among youth.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.427
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.298
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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